{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T05:07:58Z","timestamp":1764997678953,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031822247"},{"type":"electronic","value":"9783031822254"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:00:00Z","timestamp":1743120000000},"content-version":"vor","delay-in-days":86,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Process mining is a technology that helps understand, analyze, and improve processes. It has been present for around two decades, and although initially tailored for business processes,\u00a0the spectrum of analyzed processes nowadays is evermore growing. To support more complex and diverse processes, subdisciplines such as object-centric process mining\u00a0and behavioral pattern mining have emerged. Behavioral patterns allow for analyzing parts of the process in isolation, while object-centric process mining enables combining different perspectives of the process. In this work, we introduce <jats:italic>Object-Centric Local Process Models<\/jats:italic> (OCLPMs). OCLPMs are behavioral patterns tailored to analyzing complex processes where no single case notion exists\u00a0and we leverage object-centric Petri nets to model them. Additionally, we present a discovery algorithm that starts from object-centric event logs, and implement\u00a0the proposed approach in the open-source framework ProM. Finally, we demonstrate the applicability of OCLPMs in two case studies and evaluate the approach on various event logs.<\/jats:p>","DOI":"10.1007\/978-3-031-82225-4_28","type":"book-chapter","created":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T03:05:54Z","timestamp":1743303954000},"page":"376-388","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Object-Centric Local Process Models"],"prefix":"10.1007","author":[{"given":"Viki","family":"Peeva","sequence":"first","affiliation":[]},{"given":"Marvin","family":"Porsil","sequence":"additional","affiliation":[]},{"given":"Wil M. P.","family":"van der Aalst","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,28]]},"reference":[{"key":"28_CR1","doi-asserted-by":"crossref","unstructured":"van der Aalst, W.M.P., Barthelmess, P., Ellis, C.A., Wainer, J.: Workflow modeling using proclets. In: CoopIS 2000, vol. 1901, pp. 198\u2013209 (2000)","DOI":"10.1007\/10722620_20"},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"van\u00a0der Aalst, W.M.P., Berti, A.: Discovering object-centric petri nets. Fundam. Informaticae 175(1-4), 1\u201340 (2020)","DOI":"10.3233\/FI-2020-1946"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"van\u00a0der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: balancing between flexibility and support. Comput. Sci. Res. Dev. 23(2), 99\u2013113 (2009)","DOI":"10.1007\/s00450-009-0057-9"},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"Acheli, M., Grigori, D., Weidlich, M.: Efficient discovery of compact maximal behavioral patterns from event logs. In: CAiSE (2019)","DOI":"10.1007\/978-3-030-21290-2_36"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Adams, J.N., Schuster, D., Schmitz, S., Schuh, G., van\u00a0der Aalst, W.M.P.: Defining cases and variants for object-centric event data. In: ICPM 2022, pp. 128\u2013135 (2022)","DOI":"10.1109\/ICPM57379.2022.9980730"},{"key":"28_CR6","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Srikant, R.: Mining sequential patterns. In: ICDE 1995, pp. 3\u201314 (1995)","DOI":"10.1109\/ICDE.1995.380415"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Bhattacharya, K., Gerede, C.E., Hull, R., Liu, R., Su, J.: Towards formal analysis of artifact-centric business process models. In: BPM 2007, vol.\u00a04714, pp. 288\u2013304 (2007)","DOI":"10.1007\/978-3-540-75183-0_21"},{"key":"28_CR8","unstructured":"Brunings, M., Fahland, D., Verbeek, E.: Discover context-rich local process models (extended abstract). In: ICPM-D (2022)"},{"key":"28_CR9","unstructured":"Cohn, D., Hull, R.: Business artifacts: a data-centric approach to modeling business operations and processes. IEEE Data Eng. Bull. 32(3), 3\u20139 (2009)"},{"key":"28_CR10","unstructured":"van Dongen, B.: BPI challenge 2017 (2017)"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Fahland, D.: Describing behavior of processes with many-to-many interactions. In: PETRI NETS 2019, vol. 11522, pp. 3\u201324 (2019)","DOI":"10.1007\/978-3-030-21571-2_1"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"Fahland, D.: Oclets - scenario-based modeling with petri nets. In: PETRI NETS 2009, vol.\u00a05606, pp. 223\u2013242 (2009)","DOI":"10.1007\/978-3-642-02424-5_14"},{"key":"28_CR13","doi-asserted-by":"crossref","unstructured":"Fahland, D.: Process mining over multiple behavioral dimensions with event knowledge graphs. In: Process Mining Handbook, vol.\u00a0448, pp. 274\u2013319 (2022)","DOI":"10.1007\/978-3-031-08848-3_9"},{"key":"28_CR14","doi-asserted-by":"crossref","unstructured":"Ghahfarokhi, A.F., Park, G., Berti, A., van\u00a0der Aalst, W.M.P.: OCEL: a standard for object-centric event logs. In: ADBIS 2021 Short Papers, vol.\u00a01450, pp. 169\u2013175 (2021)","DOI":"10.1007\/978-3-030-85082-1_16"},{"key":"28_CR15","doi-asserted-by":"crossref","unstructured":"Haarmann, S., Lichtenstein, T., Weske, M.: Fragment-based service choreographies. In: IEEE SCC 2022, pp. 164\u2013173 (2022)","DOI":"10.1109\/SCC55611.2022.00035"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Haarmann, S., Montali, M., Weske, M.: Refining case models using cardinality constraints. In: CAiSE 2021, vol. 12751, pp. 296\u2013310 (2021)","DOI":"10.1007\/978-3-030-79382-1_18"},{"key":"28_CR17","doi-asserted-by":"crossref","unstructured":"Hewelt, M., Weske, M.: A hybrid approach for flexible case modeling and execution. In: BPM Forum 2016, vol.\u00a0260, pp. 38\u201354 (2016)","DOI":"10.1007\/978-3-319-45468-9_3"},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Leemans, M., van der Aalst, W.M.P.: Discovery of frequent episodes in event logs. In: SIMPDA 2014, Revised Selected Papers, pp. 1\u201331 (2014)","DOI":"10.1007\/978-3-319-27243-6_1"},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Li, G., de\u00a0Carvalho, R.M., van\u00a0der Aalst, W.M.P.: Automatic discovery of object-centric behavioral constraint models. In: BIS 2017, vol.\u00a0288, pp. 43\u201358 (2017)","DOI":"10.1007\/978-3-319-59336-4_4"},{"key":"28_CR20","doi-asserted-by":"crossref","unstructured":"Lu, X., Nagelkerke, M., van\u00a0de Wiel, D., Fahland, D.: Discovering interacting artifacts from ERP systems. IEEE Trans. Serv. Comput. 8(6), 861\u2013873 (2015)","DOI":"10.1109\/TSC.2015.2474358"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Mannila, H., Toivonen, H., Verkamo, A.I.: Discovery of frequent episodes in event sequences. Data Min. Knowl. Discov. 1(3), 259\u2013289 (1997)","DOI":"10.1023\/A:1009748302351"},{"key":"28_CR22","doi-asserted-by":"crossref","unstructured":"Peeva, V., Mannel, L.L., van der Aalst, W.M.P.: From place nets to local process models. In: PETRI NETS (2022)","DOI":"10.1007\/978-3-031-06653-5_18"},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Tax, N., Sidorova, N., Haakma, R., van der Aalst, W.M.P.: Mining local process models. J. Innov. Digit. Ecosyst. 3(2), 183\u2013196 (2016)","DOI":"10.1016\/j.jides.2016.11.001"}],"container-title":["Lecture Notes in Business Information Processing","Process Mining Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-82225-4_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T16:05:48Z","timestamp":1760889948000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-82225-4_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031822247","9783031822254"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-82225-4_28","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"type":"print","value":"1865-1348"},{"type":"electronic","value":"1865-1356"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"28 March 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Process Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lyngby","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Denmark","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpm2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpmconference.org\/2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}